Application Engineer

Amy's Kitchen•,

9d•$97,600 - $146,400•Hybrid

About The Position

The Application Engineer is responsible for developing, integrating, and maintaining data applications, pipelines, and processes across platforms such as Azure Data Factory, Azure Synapse, Databricks, SQL, Power BI, and Oracle BI tools. They collaborate with business analysts, internal customers, and developers to clarify requirements, design solutions, and implement features, reports, and dashboards. The role involves creating workflows that ingest, clean, and transform data from multiple sources, ensuring reliable, timely, and analytics-ready datasets. Additionally, the Data Engineer supports and administers assigned applications and ETL/ELT processes, while ensuring the organization’s data foundation is secure, efficient, and scalable to meet the needs of analysts, data scientists, and business stakeholders.

Requirements

Experience with project management and delivery methodologies.
Knowledge of report building tools and concepts.
Excellent verbal and written communication skills.
Ability to stay organized amidst multiple time demands.
Utilizing SQL, PL/SQL, DAX, Power Query (M), and shell scripting, able to create and debug a wide array of data processes, pipelines, applications, and functionality. Fluent with most essential language capabilities and syntax in the data engineering space. Able to determine and utilize appropriate design patterns.
Hands-on experience with Azure Data Factory, Azure Synapse, Databricks, ETL/ELT tools, and related data processing and warehousing tools.
Able to create builds and deployment processes according to company policy utilizing tools such as Azure DevOps and CI/CD pipelines.
Able to create complex queries in SQL, PL/SQL, and Power Query (M) languages, including joins, conditional functions, sub-selects, and other more advanced patterns against Azure SQL and Oracle databases and ERP systems (Ex: EBS and OBIEE).
Able to create and manage stored procedures, indexes, views, and transactions. Able to perform essential query performance debugging.
Strong understanding of data modeling, analytics, and reporting concepts, including databases, data warehousing, SQL, cloud services, integration strategies, and high availability/disaster recovery (HADR).
Able to write shell scripts using bash, power-shell, or similar tools. Very comfortable on the command-line for administration of Linux/Windows servers. Able manage basic services and settings (for example init scripts, registry, etc.)
Comfortable with most functions of revision control systems such as Git, SVN, and Azure DevOps. Able to manage branches and tags.
Able to lead the design, testing, and implementation phases of the SDLC in either waterfall or agile methodologies.
Can evaluate and employ security concepts such as privileged services, transport encryption, certificates.
Can describe fundamental agile principles and methodologies as well as other project management principles. Able to lead sprint planning sessions and other project and development activities for small to moderately complex projects.
Manage time and stay organized amidst multiple time demands.
Paraphrase to ensure understanding. Can explain the complex in clear terms.
Write organized, concise e-mails and other documents.
Make effective presentations across IT and to other groups.
Influence peers and customers via strong relationships and technical credibility. Rarely needs management assistance to influence laterally.
Manage effective meetings and facilitate group decisions.
Understand Amy’s basic business model, including key cost drivers and ways IT can contribute to it.
Keep current with industry trends, best practices, and market leaders.
Anticipate cross-technology and cross-functional impact of decisions and actions.
Identify root causes of problems and make data-driven decisions on solutions.
Clarify internal customer expectations and regularly check in on performance against them.
Overcome obstacles he/she can manage and seek assistance for those he/she cannot.
Four-year degree in CS or related field (or equivalent experience), or an equivalent combination of education and/or experience that demonstrates the required qualifications and skills.

Nice To Haves

Azure Data Engineer Associate
Databricks Certified Data Engineer Associate/Professional
Power BI Data Analyst Associate.

Responsibilities

Design, build, maintain, and improve custom data processes and pipelines using ETL/ELT processes to collect, process, aggregate, and transform data from various sources for both batch and real-time processing to meet business requirements.
Analyze business requirements and use cases and translate them into technical solution designs.
Employ industry standard design patterns and company practices.
Write groups of tests that exercise multiple requirements scenarios.
Suggest and document user acceptance testing and facilitate the process and training of testers. Perform acceptance testing as appropriate.
Configure and manage test automation.
Perform support for escalated support issues.
Troubleshoot data application, process, and pipeline issues by reviewing code, analyzing data, reviewing logs, and tracing code execution through multiple functions, modules, or applications. Perform root-cause-analysis of problems.
Propose and implement most bug fixes or changes to correct assigned issues. Assist in creating more complex solutions to issues found.
Participate in development planning, project management, and agile (ex: SCRUM) activities. Estimate assigned work, help to plan sprints and releases, and demonstrate completed work.
Manage revision control for owned projects. Manage release branches. Prepare deployment artifacts or packages and perform deployments and migration.
Perform refreshes and clones of supporting application and data environments per established procedures.
Identify and perform day-to-day administrative tasks in supported application and data platforms and development tooling. Support end-user administrators and IT services team.
Experience integrating AI/ML models into data pipelines using platforms such as Azure AI, Databricks, or ML frameworks to support analytics and operational use cases.
Familiarity with large language models (LLMs) and their application in data enrichment, metadata generation, and automation of data engineering tasks.
Knowledge of prompt engineering concepts and integrating AI services (e.g., APIs, Copilot, Azure OpenAI) into data workflows.
Understanding of responsible AI practices, including data privacy, bias mitigation, model governance, and security controls.
Experience operationalizing models (MLOps) including deployment, monitoring, versioning, and performance tracking.
Ability to collaborate with data scientists and business teams to productionize AI use cases and ensure scalability and reliability.
Uphold the mission of the Amy’s Food Safety and Quality Policy. This includes following all Food Safety and Sustainability programs and participating in all required training.